ArticleJournal of molecular neuroscience : MN2026
Integrated Bioinformatics and Network Analysis Identifies Key Molecular Targets and Hub Genes in Zika Virus-induced Neuroinflammation.
Article in Journal of molecular neuroscience : MN, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Zika virus (ZIKV) infection has shown significant neurodevelopmental and neurological abnormalities. However, the molecular mechanisms of ZIKV-induced neuroinflammation are poorly understood. In the current study, an integrative approach of bioinformatics analysis was used to identify the molecular targets involved in the ZIKV infection. Microarray data sets consisting of 65 samples (35 ZIKV-positive and 30 controls) from the Gene Expression Omnibus (GEO) database were used for the study. The differentially expressed genes (DEGs) analysis revealed 1,268 differentially expressed genes, of which 505 genes were up-regulated, while 763 genes were found to be down-regulated. The analysis using the weighted gene co-expression network analysis (WGCNA) revealed two modules that showed significant correlation with the ZIKV-positive samples. A total of 535 overlapping genes were used for further analysis. The protein-protein interaction (PPI) network analysis revealed ten hub genes: ITGAM, CD86, PTPRC, FCGR3A, ITGB2, TNF, ITGAX, CSF1R, CCR5, and CD4. This study suggests that the immune response plays an important role in the ZIKV infection. The study also revealed a significant enrichment of genes associated with neurogenesis, synaptic organization, axon guidance, immune response and amyloid beta binding by performing gene ontology (GO) analysis. This data potentially indicates that ZIKV infection can modulate these key hub genes to cause neuroinflammation. In addition, the study also revealed that the ZIKV infection can regulate various transcription factors and microRNAs that regulate these hub genes, indicating the complex regulatory mechanism of the ZIKV infection. Furthermore, the study revealed that the receiver operating characteristic (ROC) curve analysis showed that these hub genes, especially CCR5, are of preliminary diagnostic potential value. The study provided new insights into the molecular mechanisms of ZIKV-induced neuroinflammation and revealed the potential biomarkers and therapeutic targets of ZIKV-induced neurological disorders.
Indexed as
Identifiers
42474609What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.